CN113488995B - Shared energy storage capacity optimal configuration method and device based on energy storage cost - Google Patents
Shared energy storage capacity optimal configuration method and device based on energy storage cost Download PDFInfo
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Abstract
The invention provides a shared energy storage capacity optimal configuration method and device based on energy storage cost, wherein the method comprises the following steps: building a user side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage; constructing a user side benefit-cost partial structure objective function model based on the user side energy system operation model; determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model; the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage. The shared energy storage capacity configuration is determined by considering the energy storage cost, so that the high-efficiency utilization of the shared energy storage is facilitated, and the full utilization of the shared energy storage is realized.
Description
Technical Field
The invention relates to the technical field of novel energy sources, in particular to a shared energy storage capacity optimal configuration method and device based on energy storage cost.
Background
Today, the problems of contradiction between energy supply and demand and environmental pollution have become global problems, and the great development of new energy has become an important consensus for worldwide energy development. The comprehensive decarburization of the electric power system is regarded as the core of achieving the aim of carbon neutralization in China. In recent years, the proportion of renewable energy power generation represented by wind power and photovoltaic power generation in an electric power system is rapidly increasing, and the installed amount of distributed new energy is increasing year by year. And the distributed new energy is accessed to the user side, so that the electricity cost can be reduced. However, because of volatility and randomness of the new energy, the access of the new energy can challenge the stable operation and the power supply quality of the system, so that energy storage is often configured on a user side to improve the power consumption cost to smooth a load curve, promote the stable operation of the system and meet the power consumption requirement. However, the cost of energy storage is still relatively high, resulting in less than ideal cost effectiveness after configuration of the energy storage, although the operating cost of the system is improved.
Disclosure of Invention
The invention provides a shared energy storage capacity optimal configuration method and device based on energy storage cost, which are used for solving the defect that the prior art cannot solve cost effectiveness and realizing high-efficiency utilization of shared energy storage.
In a first aspect, the present invention provides a method for optimally configuring a shared energy storage capacity based on energy storage cost, including:
building a user side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage;
constructing a user side benefit-cost partial structure objective function model based on the user side energy system operation model;
determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model;
the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage.
The invention provides a shared energy storage capacity optimization configuration method based on energy storage cost, wherein the optimal rated capacity and rated cost of shared energy storage are determined based on a split structure objective function model of user side income-cost, and the method specifically comprises the following steps:
and under the condition that the running gain of the shared energy storage is determined by the numerator and the ratio of the proportional model of the investment cost of the shared energy storage is the maximum value, taking the rated capacity and the rated cost of the configuration corresponding to the maximum value as the rated capacity and the rated cost of the optimal shared energy storage.
The invention provides a shared energy storage capacity optimal configuration method based on energy storage cost, wherein the operation income of the shared energy storage is determined by the following method:
determining the cost of an energy system at a user side as a first cost when the shared energy storage is not configured;
determining a second cost according to the energy system cost of the user side when the shared energy storage is configured;
and determining the operation benefit of the shared energy storage through the difference value of the first cost and the second cost.
The invention provides a shared energy storage capacity optimizing configuration method based on energy storage cost, wherein the second cost is determined according to the energy system cost of a user side when the shared energy storage is configured, and the method specifically comprises the following steps:
determining a plurality of representative scenes;
determining the energy system cost of a user side in each typical scene;
determining the occurrence probability corresponding to each typical scene;
determining the actual cost of each typical scene according to the product of the energy system cost of the user side under each typical scene and the occurrence probability corresponding to each typical scene;
and determining the total cost of the plurality of typical scenes according to the actual cost of each typical scene, and taking the total cost of the plurality of typical scenes as the second cost.
The invention provides a shared energy storage capacity optimizing configuration method based on energy storage cost, wherein the operation model of the user side energy system is as follows:
wherein,power for charging the grid for the shared energy storage, +.>Is the power of the shared energy storage discharging the user, +.>Is the power actually supplied by the grid to the consumer, +.>Is the actual output of the photovoltaic, < >>Is the user load demand, < >>Is the power supplied by the grid to share the stored energy, +.>Is the power supplied by the power grid to the users, and the photovoltaic supply sharing energy storage power is +.>Photovoltaic supply consumer load power is +.>In addition, the day is divided into T time periods, delta t For the duration of each segment E m And p is as follows m To share the capacity and rated power of the stored energy E t To share the capacity of the stored energy at time t, η c And eta d To share charge/discharge efficiency of stored energy, alpha l And alpha is d To share the stored state of charge.
The invention provides a shared energy storage capacity optimizing configuration method based on energy storage cost, wherein the user side gain-cost split structure objective function model is as follows:
wherein,the cost of the energy system of the user side before the shared energy storage is configured, v av (θ) is the energy system cost of the user after the shared energy storage is configured, θ= [ p ] m ，E m ]Wherein E is m And p is as follows m To share the capacity and rated power of the stored energy, κ T Is a two-dimensional constant coefficient matrix, kappa 0 Is a constant.
In a second aspect, a shared energy storage capacity optimizing configuration device based on energy storage cost includes:
the first processing module is used for constructing a user side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage;
the second processing module is used for constructing a user side profit-cost partial structure objective function model based on the user side energy system operation model;
the third processing module is used for determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model;
the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage.
The invention provides a shared energy storage capacity optimizing configuration device based on energy storage cost, wherein the third processing module is specifically configured to:
and under the condition that the running gain of the shared energy storage is determined by the numerator and the ratio of the proportional model of the investment cost of the shared energy storage is the maximum value, taking the rated capacity and the rated cost of the configuration corresponding to the maximum value as the rated capacity and the rated cost of the optimal shared energy storage.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the steps of the shared energy storage capacity optimizing configuration method based on the energy storage cost when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the shared energy storage capacity optimizing configuration method based on energy storage costs as described in any of the above.
The shared energy storage capacity optimal configuration method and device based on the energy storage cost construct a user side energy system operation model through photovoltaic power generation, user load, a power grid interface and centralized shared energy storage; then, constructing a user side benefit-cost partial structure objective function model based on the user side energy system operation model; after the objective function model is built, determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model; the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage. According to the method, the corresponding energy storage configuration for realizing the full and efficient utilization of the shared energy storage is determined through the steps, and further, the acquired configuration can be utilized to realize the full utilization of the energy storage system.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a shared energy storage capacity optimizing configuration method based on energy storage cost;
FIG. 2 is a physical model of a shared energy storage user side energy system based on energy storage costs provided by the present invention;
FIG. 3 is a schematic structural diagram of the energy storage cost-based shared energy storage capacity optimizing configuration device provided by the invention;
fig. 4 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The following describes in conjunction with fig. 1-2 that the embodiment of the present invention provides a shared energy storage capacity optimization configuration method based on energy storage cost, including:
step 100: building a user side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage;
specifically, fig. 2 is a physical model of a user-side energy system, mainly including photovoltaic power generation, a grid interface, user loads and centralized shared energy storage. Considering that the centralized energy storage is shared by multiple users, the user load can be directly considered as the sum of multiple user loads. The electric energy generated by the photovoltaic power generation can be supplied to a load or stored in the shared energy storage system by charging the stored energy, and the rest is waste light. The load may draw power from the grid shared storage, but may not be back-sold. The shared energy storage system can be charged through a photovoltaic or power grid and can supply power to the load; the charge state and the charge and discharge power of the stored energy are limited by the upper limit and the lower limit of the stored energy. The following is specified for the physical parameters in the system: the power of the power grid for charging the stored energy isThe power of the energy storage to discharge the user is +.>The power actually supplied by the grid to the consumer is +.>The actual output of the photovoltaic is +.>The load demand is +.>The power supplied by the power grid to store energy is ∈>The power supplied to the user is +.>The photovoltaic supply energy storage power is +.>Photovoltaic supply load power is +.>
First, the power has the following relationship:
the operation constraint of the operation model of the energy system containing new energy sources of the user is as follows:
wherein a day is divided into T time periods, delta t For the duration of each segment E m And p is as follows m For energy storage capacity and rated power, E t The capacity of the energy storage at the time t; η (eta) c And eta d Alpha is the charge/discharge efficiency of energy storage l And alpha is d A lower limit and an upper limit for a state of charge (SOC) of the stored energy; (2 a) constraining the primary variable to remain non-negative at all times. (2b) The charge and discharge power of the stored energy cannot exceed the power capacity p m . (2 c) describes the change in the state of charge of the stored energy. (2 d) constraining the state of charge upper and lower limits.
Step 200: constructing a user side benefit-cost partial structure objective function model based on the user side energy system operation model;
specifically, the user side benefit-cost partial structure objective function model is formed by constructing an operation benefit with a numerator being the shared energy storage, and a denominator being a proportional model of the investment cost of the shared energy storage. Based on the operation model of the energy system containing new energy at the user side established in the previous step 100, the investment cost and the operation benefit of energy storage are further considered.
The cost before and after energy storage is configured as v av (0) And v av (θ) for θ > 0, and is guaranteed to have
The energy storage investment cost is as follows:
C invest ＝κ p p m +κ e E m +κ 0 ＝κ T θ+κ 0 (4)
thus, by considering the user-side benefit-cost partial structure objective function, the following can be established
Step 300: determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model;
specifically, the method for solving the shared energy storage capacity value evaluation model aims to directly obtain an expression of an optimal value function v (theta). This needs to overcome the operational efficiency problems of the split-architecture non-convex and scene-based approach.
First, for any fixed parameter θ, the dual problem of considering problem (3) is that because of the lack of explicit expression of cost with respect to decision variable θ
Due to the strong duality, the original problem (3) and the dual problem (6) have the same optimal value function v av (θ). Taking into account v av (θ) is a convex function with respect to θ, thus-v av And (θ) is concave. At the same time, C invest Always as a linear function. Because the feasible region is a polyhedron and the objective function is pseudo-concave, each stationary point is a globally optimal solution for the objective, and therefore the use of a local solution algorithm is considered to improve the operating efficiency.
If there are enough sampling points theta i Corresponding to the dual variable mu i ，v i . Thus, v in problem (5) av (θ) can be replaced by a scalar by adding a facet:
bringing (7) into question (5), the following is obtained:
wherein,n＝B T v i 。
performing variable substitution operation on the problem 8, and converting the problem equivalence into a linear problem:
the transformed linear programming problem can be directly solved to obtain a configuration parameter theta= [ p ] m ，E m ]。
It is apparent that the above method is well suited for iterative solutions to find optimal configurations, directly yielding cost-effective solutions.
The shared energy storage capacity optimizing configuration method based on the energy storage cost constructs a user side energy system operation model through photovoltaic power generation, user load, a power grid interface and centralized shared energy storage; then, constructing a user side benefit-cost partial structure objective function model based on the user side energy system operation model; after the objective function model is built, determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model; the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage. According to the method, the corresponding energy storage configuration for realizing the full and efficient utilization of the shared energy storage is determined through the steps, and further, the acquired configuration can be utilized to realize the full utilization of the energy storage system.
According to an embodiment of the present invention, there is provided a method for optimally configuring a shared energy storage capacity based on energy storage cost, where the determining, based on the user side profit-cost split structure objective function model, an optimal rated capacity and rated cost of the shared energy storage specifically includes:
and under the condition that the running gain of the shared energy storage is determined by the numerator and the ratio of the proportional model of the investment cost of the shared energy storage is the maximum value, taking the rated capacity and the rated cost of the configuration corresponding to the maximum value as the rated capacity and the rated cost of the optimal shared energy storage.
Specifically, since the numerator of the objective function model with the user-side gain-cost division structure is the running gain of the shared energy storage, and the denominator is the largest ratio of the investment cost of the shared energy storage, that is, the highest gain ratio of the objective function model, the rated capacity configured for obtaining the gain ratio and the rated cost are the optimal condition.
According to the embodiment of the invention, the shared energy storage capacity optimizing configuration method based on the energy storage cost is provided, wherein the operation income of the shared energy storage is determined by the following method:
determining the cost of an energy system at a user side as a first cost when the shared energy storage is not configured;
determining a second cost according to the energy system cost of the user side when the shared energy storage is configured;
and determining the operation benefit of the shared energy storage through the difference value of the first cost and the second cost.
Specifically, the running benefit of the shared energy storage is embodied by judging whether the shared energy storage is configured or not, namely, the cost of the energy system at the user side when the shared energy storage is not configured and the cost of the energy system at the user side after the shared energy storage is configured, and the difference value between the cost and the cost is the benefit brought by the configuration of the shared energy storage.
According to an embodiment of the present invention, a method for optimally configuring a shared energy storage capacity based on energy storage cost is provided, where the determining a second cost according to energy system cost at a user side when configuring the shared energy storage specifically includes:
determining a plurality of representative scenes;
determining the energy system cost of a user side in each typical scene;
determining the occurrence probability corresponding to each typical scene;
determining the actual cost of each typical scene according to the product of the energy system cost of the user side under each typical scene and the occurrence probability corresponding to each typical scene;
and determining the total cost of the plurality of typical scenes according to the actual cost of each typical scene, and taking the total cost of the plurality of typical scenes as the second cost.
Specifically, consider that electricity prices use time-and-level-of-use to avoid a drastic change in load when electricity prices are slightly lower. Xi is constant:
since optimization problems are more problematic, the construction of the main variables in a compact form is performed. Defining a power flow related variable:
parameter decision variables to be configured:
θ＝[p m ，E m ] (12)
then, after proper transformation treatment, the cost of the system containing new energy at the user side can be expressed as follows:
wherein,is a matrix generated based on energy storage operation constraints, v (θ) is an optimal value function.
Further, by taking into account the uncertainty in the new energy, the scene method is mainly utilized. By selecting S typical days, the probability of occurrence for each typical day is different, as is the force profile. The running cost of the system in the scene s is as follows:
consider the probability of the scene correspondence to be ρ s The following are considered only for the problem of running costs:
referring to fig. 3, an embodiment of the present invention provides a shared energy storage capacity optimizing configuration device based on energy storage cost, including:
the first processing module 31 is configured to construct a user-side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage;
a second processing module 32, configured to construct a user side benefit-cost split structure objective function model based on the user side energy system operation model;
a third processing module 33, configured to determine an optimal rated capacity and rated cost of the shared energy storage based on the user-side profit-cost split structure objective function model;
the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage.
Since the apparatus provided by the embodiment of the present invention may be used to perform the method described in the above embodiment, its working principle and beneficial effects are similar, so that details will not be described herein, and reference will be made to the description of the above embodiment.
The embodiment of the invention provides a shared energy storage capacity optimizing configuration device based on energy storage cost, wherein the third processing module 32 is specifically configured to:
and under the condition that the running gain of the shared energy storage is determined by the numerator and the ratio of the proportional model of the investment cost of the shared energy storage is the maximum value, taking the rated capacity and the rated cost of the configuration corresponding to the maximum value as the rated capacity and the rated cost of the optimal shared energy storage.
The embodiment of the invention provides a shared energy storage capacity optimizing configuration device based on energy storage cost, wherein the second processing module 32 is further configured to:
determining the cost of an energy system at a user side as a first cost when the shared energy storage is not configured;
determining a second cost according to the energy system cost of the user side when the shared energy storage is configured;
and determining the operation benefit of the shared energy storage through the difference value of the first cost and the second cost.
The present invention provides a shared energy storage capacity optimizing configuration device based on energy storage cost, wherein the second processing module 32 is further configured to:
determining a plurality of representative scenes;
determining the energy system cost of a user side in each typical scene;
determining the occurrence probability corresponding to each typical scene;
determining the actual cost of each typical scene according to the product of the energy system cost of the user side under each typical scene and the occurrence probability corresponding to each typical scene;
and determining the total cost of the plurality of typical scenes according to the actual cost of each typical scene, and taking the total cost of the plurality of typical scenes as the second cost.
The present invention provides a shared energy storage capacity optimizing configuration device based on energy storage cost, wherein the first processing module 31 is configured to construct a user side energy system operation model as follows:
wherein,power for charging the grid for the shared energy storage, +.>Is the power of the shared energy storage discharging the user, +.>Is the power actually supplied by the grid to the consumer, +.>Is the actual output of the photovoltaic, < >>Is the user load demand, < >>Is the power supplied by the grid to share the stored energy, +.>Is the power supplied by the power grid to the users, and the photovoltaic supply sharing energy storage power is +.>Photovoltaic supply consumer load power is +.>In addition, the day is divided into T time periods, delta t For the duration of each segment E m And p is as follows m To share the capacity and rated power of the stored energy E t To share the capacity of the stored energy at time t, η c And eta d To share charge/discharge efficiency of stored energy, alpha l And alpha is d To share the stored state of charge.
The embodiment of the invention provides a shared energy storage capacity optimizing configuration device based on energy storage cost, wherein the second processing module 32 is configured to construct a user side profit-cost split structure objective function model as follows:
wherein,the cost of the energy system of the user side before the shared energy storage is configured, v av (θ) is the energy system cost of the user after the shared energy storage is configured, θ= [ p ] m ，E m ]Wherein E is m And p is as follows m To share the capacity and rated power of the stored energy, κ T Is a two-dimensional constant coefficient matrix, kappa 0 Is a constant.
Fig. 4 illustrates a physical schematic diagram of an electronic device, as shown in fig. 4, which may include: processor 410, communication interface (Communications Interface) 420, memory 430 and communication bus 440, wherein processor 410, communication interface 420 and memory 430 communicate with each other via communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform a shared energy storage capacity optimization configuration method based on energy storage costs, the method comprising: building a user side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage; constructing a user side benefit-cost partial structure objective function model based on the user side energy system operation model; determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model; the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage.
Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the method of shared energy storage capacity optimization configuration based on energy storage costs provided by the above methods, the method comprising: building a user side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage; constructing a user side benefit-cost partial structure objective function model based on the user side energy system operation model; determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model; the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage.
In yet another aspect, the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the above provided shared energy storage capacity optimization configuration method based on energy storage costs, the method comprising: building a user side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage; constructing a user side benefit-cost partial structure objective function model based on the user side energy system operation model; determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model; the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. The shared energy storage capacity optimizing configuration method based on the energy storage cost is characterized by comprising the following steps of:
building a user side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage;
constructing a user side benefit-cost partial structure objective function model based on the user side energy system operation model;
determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model;
the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage;
the construction of the user side energy system operation model based on photovoltaic power generation, user load, power grid interfaces and centralized shared energy storage comprises the following steps:
the user side energy system physical model mainly comprises photovoltaic power generation, a power grid interface, user load and centralized shared energy storage; considering that the centralized shared energy storage is shared by multiple users, the user load can be directly considered as the sum of multiple user loads; the electric energy generated by the photovoltaic power generation can be supplied to a load or stored in a shared energy storage system by charging energy storage, and the rest is waste light; the load can share energy from the power grid to obtain electric energy, but cannot be reversely sold; the shared energy storage system can be charged through a photovoltaic or power grid and can supply power to the load; the charge state and the charge and discharge power of the stored energy are limited by the upper limit and the lower limit of the stored energy; the following is specified for the physical parameters in the system: the power of the power grid for charging the stored energy isThe power of the energy storage to discharge the user is +.>The power actually supplied by the grid to the consumer is +.>The actual output of the photovoltaic is +.>The load demand is +.>The power supplied by the power grid to store energy is ∈>The power supplied to the user is +.>The photovoltaic supply energy storage power isPhotovoltaic supply load power is +.>
First, the power has the following relationship:
the operation constraint of the operation model of the energy system containing new energy sources of the user is as follows:
wherein a day is divided into T time periods, delta t For the duration of each segment E m And p is as follows m For energy storage capacity and rated power, E t The capacity of the energy storage at the time t; η (eta) c And eta d Alpha is the charge/discharge efficiency of energy storage l And alpha is d A lower limit and an upper limit for a state of charge (SOC) of the stored energy; (2a) Restraining the main variable to be always non-negative, (2 b) the energy storage charge-discharge power cannot exceed the power capacity p m (2 c) describes the change in the stored state of charge and (2 d) constrains the upper and lower limits of the state of charge.
2. The energy storage cost-based shared energy storage capacity optimization configuration method according to claim 1, wherein the determining the optimal rated capacity and rated cost of the shared energy storage based on the user-side profit-cost split structure objective function model specifically comprises:
and under the condition that the running gain of the shared energy storage is determined by the numerator and the ratio of the proportional model of the investment cost of the shared energy storage is the maximum value, taking the rated capacity and the rated cost of the configuration corresponding to the maximum value as the rated capacity and the rated cost of the optimal shared energy storage.
3. The energy storage cost-based shared energy storage capacity optimal configuration method according to claim 1, wherein the operation benefit of the shared energy storage is determined by the following method:
determining the cost of an energy system at a user side as a first cost when the shared energy storage is not configured;
determining a second cost according to the energy system cost of the user side when the shared energy storage is configured;
and determining the operation benefit of the shared energy storage through the difference value of the first cost and the second cost.
4. The energy storage cost-based shared energy storage capacity optimization configuration method according to claim 3, wherein the determining the second cost according to the energy system cost of the user side when configuring the shared energy storage specifically comprises:
determining a plurality of representative scenes;
determining the energy system cost of a user side in each typical scene;
determining the occurrence probability corresponding to each typical scene;
determining the actual cost of each typical scene according to the product of the energy system cost of the user side under each typical scene and the occurrence probability corresponding to each typical scene;
and determining the total cost of the plurality of typical scenes according to the actual cost of each typical scene, and taking the total cost of the plurality of typical scenes as the second cost.
5. The energy storage cost-based shared energy storage capacity optimization configuration method according to claim 1, wherein the user side benefit-cost split structure objective function model is:
wherein,the cost of the energy system of the user side before the shared energy storage is configured, v av (θ) is the energy system cost of the user after the shared energy storage is configured, θ= [ p ] m ，E m ]Wherein E is m And p is as follows m To share the capacity and rated power of the stored energy, κ T Is a two-dimensional constant coefficient matrix, kappa 0 Is a constant.
6. The utility model provides a sharing energy storage capacity optimal configuration device based on energy storage cost which characterized in that includes:
the first processing module is used for constructing a user side energy system operation model based on photovoltaic power generation, user load, a power grid interface and centralized shared energy storage;
the second processing module is used for constructing a user side profit-cost partial structure objective function model based on the user side energy system operation model;
the third processing module is used for determining the optimal rated capacity and rated cost of the shared energy storage based on the user side profit-cost split structure objective function model;
the user side benefit-cost partial structure objective function model is formed by constructing a proportional model with a numerator which is the operation benefit of the shared energy storage and a denominator which is the investment cost of the shared energy storage;
the construction of the user side energy system operation model based on photovoltaic power generation, user load, power grid interfaces and centralized shared energy storage comprises the following steps:
the user side energy system physical model mainly comprises photovoltaic power generation, a power grid interface, user load and centralized shared energy storage; considering that the centralized shared energy storage is shared by multiple users, the user load can be directly considered as the sum of multiple user loads; the electric energy generated by the photovoltaic power generation can be supplied to a load or stored in a shared energy storage system by charging energy storage, and the rest is waste light; the load can share energy from the power grid to obtain electric energy, but cannot be reversely sold; the shared energy storage system can be charged through a photovoltaic or power grid and can supply power to the load; the charge state and the charge and discharge power of the stored energy are limited by the upper limit and the lower limit of the stored energy; the following is specified for the physical parameters in the system: the power of the power grid for charging the stored energy isThe power of the energy storage to discharge the user is +.>The power actually supplied by the grid to the consumer is +.>The actual output of the photovoltaic isThe load demand is +.>The power supplied by the power grid to store energy is ∈>The power supplied to the user is +.>The photovoltaic supply energy storage power is +.>Photovoltaic supply load power is +.>
First, the power has the following relationship:
the operation constraint of the operation model of the energy system containing new energy sources of the user is as follows:
wherein a day is divided into T time periods, delta t For the duration of each segment E m And p is as follows m For energy storage capacity and rated power, E t The capacity of the energy storage at the time t; η (eta) c And eta d Alpha is the charge/discharge efficiency of energy storage l And alpha is d A lower limit and an upper limit for a state of charge (SOC) of the stored energy; (2a) Restraining the main variable to be always non-negative, (2 b) the energy storage charge-discharge power cannot exceed the power capacity p m (2 c) describes the change in the stored state of charge and (2 d) constrains the upper and lower limits of the state of charge.
7. The energy storage cost-based shared energy storage capacity optimal configuration device according to claim 6, wherein the third processing module is specifically configured to:
and under the condition that the running gain of the shared energy storage is determined by the numerator and the ratio of the proportional model of the investment cost of the shared energy storage is the maximum value, taking the rated capacity and the rated cost of the configuration corresponding to the maximum value as the rated capacity and the rated cost of the optimal shared energy storage.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the energy storage cost based shared energy storage capacity optimization configuration method according to any of claims 1 to 5 when the program is executed by the processor.
9. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the energy storage cost based shared energy storage capacity optimization configuration method of any of claims 1 to 5.
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